MATLAB: Neural Network tool nftool

neural networksnftool

1. Once a network is trained how can it be used to find new outputs from known inputs?
2. There is a problem ….When I use nftool with some data set (having 5-dimensional inputs and 4-dimensional outputs) It fit very well. nftool takes 1000 iteration for it. and performance is very well around e-02….. But When I use advanced script generated by nftool, or When I write my own code for the same. It takes 12-20 iteration and performance is as high as e+06 to e+07.
Where is the problem?
Please help !

Best Answer

Not enough information.
 1. Your spelling of outputs is inconsistent
 2. [ I N ] = size(inputs) =?   
 3  [ O N ] = size(outputs) = ?
 4. MSE00 = mean(var(outputs'),1) = ?   % Reference MSE 
 5. Ntrn = N - 2*(0.15*N)   % Default No. of training examples 
 6. Ntrneq = Ntrn*O         % No. of training equations
 7. H = 10 % default No. of hidden nodes
 8. Nw = (I+1)*H+(H+1)*O % No. of unknown weights to be estimated from Ntrneq
 9. In order to avoid a poor set of initial random weights, obtain Ntrials = 10 
separate designs by looping over i = 1:Ntrials
 10. Pick the best design with the lowest normalized VALIDATION MSE
     NMSEval = tr.best_vperf/MSE00   % Desire 0 < NMSEval << 1
Hope this helps.
Thank you for formally accepting my answer
Greg
P.S. Search on greg i=1:Ntrials
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